Optimal Capacity and Placement of Microgrids for Resiliency Enhancement of Distribution Networks Under Extreme Weather Events

被引:2
|
作者
Borghei, Moein [1 ]
Ghassemi, Mona [1 ]
Liu, Chen-Ching [1 ]
机构
[1] Virginia Tech, Power & Energy Ctr, Bradley Dept Elect & Comp Engn, Blacksburg, VA 24061 USA
关键词
Optimal capacity and placement of microgrids; switching operations; critical loads; resiliency enhancement; extreme weather events; POWER; RESTORATION;
D O I
10.1109/isgt45199.2020.9087693
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When a fault or a series of faults occur in a distribution network, it is of considerable significance to feeding loads, most importantly critical loads. Although network reconfiguration by switching operations has been usually considered as a relatively low-cost method for load restoration, it alone may not able to restore critical loads under extreme weather events such as hurricanes where multiple faults can happen within the network. Under such severe circumstances, one of the complementary methods for service restoration is benefiting from existing installed microgrids. In this paper, the idea of planning future microgrids-in terms of optimal location and capacity- in combination with switching operations to restore critical loads, for the first time, is considered. To this planning-operation concept end, a graph-theoretic method is developed to find optimal switching operations coupled with a heuristic optimization method developed to determine future microgrids' location and capacity to maximize the resiliency of the network while keeping the associated cost with distributed generations (DGs) in microgrids as low as possible. Simulations results on the modified IEEE 37-node distribution network show the effectiveness of the proposed idea. Moreover, using appropriate reduction techniques, the computational efficacy of the method has also been greatly improved.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] Optimal placement of rain gauge networks in complex terrains for monitoring extreme rainfall events: a review
    Ankur Suri
    Sarita Azad
    Theoretical and Applied Climatology, 2024, 155 : 2511 - 2521
  • [22] Probabilistic Planning of Distribution Networks With Optimal DG Placement Under Uncertainties
    Das, Soumya
    Fosso, Olav Bjarte
    Marafioti, Giancarlo
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2023, 59 (03) : 2731 - 2741
  • [23] Extreme weather events in Iran under a changing climate
    Alizadeh-Choobari, Omid
    Najafi, M. S.
    CLIMATE DYNAMICS, 2018, 50 (1-2) : 249 - 260
  • [24] Extreme weather events in Iran under a changing climate
    Omid Alizadeh-Choobari
    M. S. Najafi
    Climate Dynamics, 2018, 50 : 249 - 260
  • [25] A Cooperative Generation Expansion Planning of Microgrids to Improve the Resiliency of Active Distribution Networks
    Atazadegan, Mohammad Hossein
    Rokrok, Esmaeel
    Doostizadeh, Meysam
    IEEE ACCESS, 2024, 12 : 192230 - 192249
  • [26] Optimal capacitor placement in distribution networks
    Sharaf, AM
    Ibrahim, ST
    ELECTRIC POWER SYSTEMS RESEARCH, 1996, 37 (03) : 181 - 187
  • [27] Optimal PMU Placement for Distribution Networks
    Mabaning, Abdul Aziz G.
    Orillaza, Jordan Rel C.
    von Meier, Alexandra
    2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 2017, : 577 - 582
  • [28] Secondary control fusion in inverter intensive dynamic microgrids for distribution system resiliency enhancement
    Men, Yuxi
    Ding, Lizhi
    Zhang, Junhui
    Lu, Xiaonan
    IENERGY, 2023, 2 (01): : 9 - 13
  • [29] Optimal Capacity and Location for Renewable-based Microgrids Considering Economic Planning in Distribution Networks
    Aazami R.
    Dabestani S.
    Shirkhani M.
    International Journal of Engineering, Transactions A: Basics, 2023, 36 (12): : 2175 - 2183
  • [30] Age-dependent resilience assessment and quantification of distribution systems under extreme weather events
    Dehghani, Farshid
    Mohammadi, Mohammad
    Karimi, Mazaher
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2023, 150